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27th Pan-Hellenic Conference on Progress in Computing and informatics with International Participation, PCI 2023

作者： Voutos, Yorghos Palamas, Stergios Mylonas, Phivos Department of Informatics and Computer Engineering University of West Attica Greece Department of Informatics Ionian University Greece

ISBN: (纸本)9798400716263

In the context of promoting environmental wealth to visitors, this paper explores the development of a web platform, widening the visibility of local biodiversity and aiding in its preservation. We introduce a modular web platform, constructed from interconnected front-end and back-end modules and built upon open-source technologies. In the past, delivering captivating, media-rich user experiences, called for specific hardware and proprietary development tools. This study highlights how the latest in web technology, combined with contemporary web browsers (such as those supporting the WebGL standard), now allows for the rollout of these advanced services on everyday mobile devices using widely accepted web technologies like HTML, CSS, and JavaScript. The immersive qualities of multimedia and cutting-edge AR/VR technologies have enhanced the magic of natural sites and the attractiveness of points of interest. Under this notion, we've worked on a thorough investigation of how these paradigm-shifting discoveries might be used to make a virtual retreat for enthusiasts of ecology. The proposed platform's focus on the protection and promotion of biodiversity is the basis of not only improving the user experience but it also emerges as a tool for the preservation of the Ionian Islands' natural marvels as we delve into its architecture and capabilities. © 2023 Owner/Author.

关键词： Biodiversity

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Flexible Real-Time Emulation of Fading Channels on SoC-FPGA Devices

Flexible Real-Time Emulation of Fading Channels on SoC-FPGA ...

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2024 Panhellenic Conference on Electronics and Telecommunications, PACET 2024

作者： Papalamprou, Ilias Armeniakos, Giorgos Stratakos, Ioannis Lentaris, George Soudris, Dimitrios National Technical University of Athens School of Electrical and Computer Engineering Greece University of West Attica Department of Informatics and Computer Engineering Greece

ISBN: (纸本)9798350318845

Modeling and replicating the channel effects between a transmitter and receiver, is crucial in any telecommunication system, in order to evaluate the impact on the transmitted data. Therefore the necessity of having access to a real time channel emulator is vital. In order to meet these constraints, in this work we present a flexible, high performance and resource efficient FPGA-based channel emulator, focusing on fading models. Additionally, we perform a trade-off analysis between bit accuracy, resources utilization and system's accuracy in terms of Mean Relative Error and the Probability Density Function. Our study shows that by using a circuit with reduced bit-widths, we can achieve 24%-46% reduction in various resources, while preserving the algorithmic accuracy of the channel emulator and operating at a throughput of 500Msps. © 2024 IEEE.

关键词： Fading channels

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Distributed computing and shared memory-based utility list buffer miner with parallel frameworks for high utility itemset mining

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International Journal of Business Intelligence and Data Mining 2023年第2期23卷 125-149页

作者： Atmaja, Eduardus Hardika Sandy Sonawane, Kavita Department of Computer Engineering St. Francis Institute of Technology Mumbai India Department of Informatics Sanata Dharma University Yogyakarta Indonesia

High utility itemset mining (HUIM) is a well-known pattern mining technique. It considers the utility of the items that leads to finding high profit patterns which are more useful for real conditions. Handling large and complex dataset are the major challenges in HUIM. The main problem here is the exponential time complexity. Literature review shows multi-core approaches to solve this problem by parallelising the tasks, but it is limited to single machine resources and also needs a novel strategy. To address this problem, we proposed new strategies namely distributed computing (DC-PLB) and shared memory (SM-PLB)-based utility list buffer miner with parallel frameworks (PLB). It utilises cluster nodes to parallelise and distribute the tasks efficiently. Thorough experiments with results proved that the proposed frameworks achieved better runtime (448 s) in dense datasets compared to the existing PLB (2,237 s). It has effectively addressed the challenges of handing large and complex datasets. © 2023 Inderscience Enterprises Ltd.

关键词： Data mining

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Multiclass Imbalance Resampling Techniques for Network Intrusion Detection 10

Multiclass Imbalance Resampling Techniques for Network Intru...

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10th International Conference on Smart Computing and Communication, ICSCC 2024

作者： Saharuna, Zawiyah Ahmad, Tohari Institut Teknologi Sepuluh November Department of Informatics Surabaya Indonesia Politeknik Negeri Ujung Pandang Department of Informatics & Computer Engineering Makassar Indonesia

ISBN: (纸本)9798350363104

Security datasets often exhibit significant imbalances that can introduce bias during model training, diminish sensitivity to actual attacks, and lead to a substantial number of false negatives, potentially overlooking real threats. This is particularly evident in the highly skewed distribution of the UNSW-NB18 Bot-IoT dataset. To mitigate these issues, this study proposes implementing either Random Oversampling (ROS) or Synthetic Minority Oversampling (SMOTE) in conjunction with five ensemble algorithms to develop models for predicting intrusions in the Internet of Things networks. The results show that incorporating these methods with ensemble learners significantly improves model accuracy by 1 % to 4 % across the four algorithms compared to their absence. In addition, there were dramatic increases in precision, recall, and F1-score, achieving values between 95% and 100%. © 2024 IEEE.

关键词： Network intrusion

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Application of Artificial Intelligence for Maternal and Child Disorders in Indonesia: A Review 22nd

Application of Artificial Intelligence for Maternal and Chil...

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22nd Asia Simulation Conference, AsiaSim 2023

作者： Kurnianingtyas, Diva Indriati Muflikhah, Lailil Department of Informatics Engineering Faculty of Computer Science Universitas Brawijaya Malang65145 Indonesia

ISBN: (纸本)9789819972395

The development of Artificial Intelligence (AI) technology is used to minimize the risk of maternal disorders during pregnancy. Maternal health needs to be monitored so as not to cause problems during the baby's birth. The purpose of this study is to provide a literature review from 2017 to 2023. The method used is Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). This study is a basis for researchers to help solve maternal health problems using AI. This technology is proven to detect and predict problems during pregnancy, thereby reducing maternal and infant mortality and preventing abnormalities in the development process. In addition, AI can help improve medical personnel's performance by minimizing human error. This study also presents trends in AI problems and methods used. However, the rapid development of AI methods has not provided novelty in solving maternal pregnancy issues because researchers rarely implement them on a wider scope of problems. Furthermore, it needs to be developed with other methods, such as simulation. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Obstetrics

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Extending Online 4D Situational Awareness in Connected and Automated Vehicles

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2023年第8期9卷 1-19页

作者： Piperigkos, Nikos Anagnostopoulos, Christos Lalos, Aris S. Berberidis, Kostas Computer Engineering and Informatics Department University of Patras Greece Industrial Systems Institute ATHENA Research Center Patras Greece

Empowering each vehicle with four dimensional (4D) situational awareness, i.e., accurate knowledge of neighboring vehicles' 3D locations over time in a cooperative manner (instead of focusing only on self-localization), is fundamental for improving autonomous driving performance in diverse traffic conditions. For this task, identification, localization and tracking of nearby road users is critical for enhancing safety, motion planning and energy consumption of automated vehicles. Advanced perception sensors as well as communication abilities, enable the close collaboration of moving vehicles and other road users, and significantly increase the positioning accuracy via multi-modal sensor fusion. The challenge here is to actually match the extracted measurements from perception sensors with the correct vehicle ID, through data association. In this paper, two novel and distributed Cooperative Localization or Awareness algorithms are formulated, based on linear least-squares minimization and the celebrated Kalman Filter. They both aim to improve ego vehicle's 4D situational awareness, so as to be fully location aware of its surrounding and not just its own position. For that purpose, ego vehicle forms a star like topology with its neighbors, and fuses four types of multi-modal inter-vehicular measurements (position, distance, azimuth and inclination angle) via the linear Graph Laplacian operator and geometry capturing differential coordinates. Moreover, a data association strategy has been integrated to the algorithms as part of the identification process, which is shown to be much more beneficial than traditional Hungarian algorithm. An extensive experimental study has been conducted in CARLA, SUMO and Artery simulators, highlighting the benefits of the proposed methods in a variety of experimental scenarios, and verifying increased situational awareness ability. The proposed distributed approaches offer high positioning accuracy, outperforming other state-of-the-art c

关键词： Laplace equation

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Integrating Stereotype User Models for Adaptive Scenarios in Game Playing within Immersive Virtual Environments 18

Integrating Stereotype User Models for Adaptive Scenarios in...

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18th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2023

作者： Strousopoulos, Panagiotis Troussas, Christos Krouska, Akrivi Mylonas, Phivos Sgouropoulou, Cleo University of West Attica Department of Informatics and Computer Engineering Greece

ISBN: (纸本)9798350327717

Stereotypes constitute a widely used technique for creating user models. This paper explores the potential of stereotype-based models in virtual environments in order to enhance user engagement and learning outcomes. The focus is on an application, named Beekeeper World, which employs adaptive scenarios that respond to user actions. These scenarios, referred to as stereotype user models, represent predefined behavior patterns that Beekeeper World uses to respond to specific user actions. In the game context, these stereotypes are triggered by particular player interactions involving the ecological dynamics of bees and spiders. The first one challenges the player when s/he fails to protect a bee by strengthening the enemy spider. The second stereotype is a way of helping the player by pausing the spiders' spawning when s/he cannot defend the bees. These stereotypes can be instrumental in creating predictable, consistent behavior in Beekeeper World. They provide a framework for the system to respond to various user inputs in a consistent manner. This consistency can be crucial in maintaining the desired user engagement, as it ensures that the system's responses align with the user's expectations based on their previous interactions. Furthermore, these stereotypes can contribute to the complexity and challenge of the game, as they require the player to understand and adapt to these patterns in order to succeed, thereby promoting strategic thinking and problem-solving skills. © 2023 IEEE.

关键词： Virtual reality

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Maintaining Text Legibility Regarding Font Size Based on User Distance in Mobile Devices: Application Development and User Evaluation

Maintaining Text Legibility Regarding Font Size Based on Use...

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2023 IEEE International Symposium on Multimedia, ISM 2023

作者： Mallas, Andreas Papadatou, Hara Xenos, Michalis University of Patras Department of Computer Engineering and Informatics Patras Greece

ISBN: (纸本)9798350395761

The text's legibility can dramatically influence any device's usability, and a wealth of research has examined the ideal font characteristics for various displays regarding legibility and readability. However, mobile devices have an additional factor that influences viewing conditions;their greatest strength, i.e., portability, is their biggest weakness in this regard. Furthermore, the freedom to use the device in diverse situations and positions (sitting, standing, in transit, or while waiting in line) can influence various facets related to legibility, such as the user's holding position, operating style, and the environment's light directed to the phone. The application developed aims to maintain user-preferred text font size -in all typical distances that users operate their phones- by automatically adjusting the font size according to the distance between the user and the device by using the device's camera to calculate the distance in real-time. A two-part experiment (n = 34) revealed that the application scored an excellent usability score while the visual landmarks used showed a promising start at addressing an issue related to our approach. © 2023 IEEE.

关键词： Display devices

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Novel Framework of Segmentation 3D MRI of Brain Tumors

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computers, Materials & Continua 2023年第2期74卷 3489-3502页

作者： Ibrahim Mahmoud El-Henawy Mostafa Elbaz Zainab H.Ali Noha Sakr Department of Computer Science Faculty of Computers and InformaticsZagazig UniversityZagazigEgypt Department of Computer Science Faculty of Computers and InformaticsKafrelsheikh UniversityKafrelsheikhEgypt Department of Embedded Network Sys.and Tec. Faculty of Artificial IntelligenceKafrelsheikh UniversityKafrelsheikhEgypt Computers Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansouraEgypt

Medical image segmentation is a crucial process for computer-aided diagnosis and *** image segmentation refers to portioning the images into small,disjointed parts for simplifying the processes of analysis and *** and speckle noise are different types of noise in magnetic resonance imaging(MRI)that affect the accuracy of the segmentation process ***,image enhancement has a significant role in MRI *** paper proposes a novel framework that uses 3D MRI images from Kaggle and applies different diverse models to remove Rician and speckle noise using the best possible noise-free *** proposed techniques consider the values of Peak Signal to Noise Ratio(PSNR)and the level of noise as inputs to the attention-U-Net model for segmentation of the *** framework has been divided into three stages:removing speckle and Rician noise,the segmentation stage,and the feature extraction *** framework presents solutions for each problem at a different stage of the *** the first stage,the framework uses Vibrational Mode Decomposition(VMD)along with Block-matching and 3D filtering(Bm3D)algorithms to remove the ***,the most significant Rician noise-free images are passed to the three different methods:Deep Residual Network(DeRNet),Dilated Convolution Auto-encoder Denoising Network(Di-Conv-AE-Net),andDenoising Generative Adversarial Network(DGAN-Net)for removing the speckle *** Bm3D have achieved PSNR values for levels of noise(0,0.25,0.5,0.75)for reducing the Rician noise by(35.243,32.135,28.214,24.124)and(36.11,31.212,26.215,24.123)*** framework also achieved PSNR values for removing the speckle noise process for each level as follows:(34.146,30.313,28.125,24.001),(33.112,29.103,27.110,24.194),and(32.113,28.017,26.193,23.121)forDeRNet,Di-Conv-AE-Net,and DGAN-Net,*** experiments that have been conducted have proved the efficiency of the proposed framework a

关键词： MRI Rician noise speckle noise segmentation deep learning

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Influence Maximization in Dynamic Social Networks Under Partially Observable Environments

Influence Maximization in Dynamic Social Networks Under Part...

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2023 Congress in computer Science, computer engineering, and Applied Computing, CSCE 2023

作者： Smani, Gkolfo I. Megalooikonomou, Vasileios University of Patras Department of Computer Engineering and Informatics Patras Greece

ISBN: (纸本)9798350327595

Influence and influence diffusion have been studied widely in social networks. Influence maximization is the problem of detecting a set of influential nodes in a social network, which represents relationships among individuals. Although, most of the existing works on this task focus on static networks, in this paper we study the problem of influence maximization in dynamic social networks where the changes that occur over time can be observed by periodically probing nodes to update their connections. The goal of this work is to probe a subset of nodes in a social network so that the actual influence diffusion process in the network can be best uncovered with the probing nodes. We propose three algorithms, MaxC, MaxDC and MaxT, to approximate the optimal solution with probing nodes, which achieve improvement on estimating the number of activated nodes over state-of-the-art-method by 2.88%, 4.95% and 5.39%, respectively. © 2023 IEEE.

关键词： core number diffusion dynamic social networks graphs maximization influence probing social influence trussness

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